A hybrid object based model combining probability and fuzzy set theories. (15th January 2008)

• Record Type: Journal Article
• Authors: Cao, Tru H.; Nguyen, Hoa
• Is Part Of: International journal of intelligent information and database systems. Volume 1:Number 3/4(2007)
• Page Start: 386
• Page End: 406
• Publication Date: 2008-01-15
• Subjects: object-oriented modelling -- probability distribution -- fuzzy sets -- class methods -- selection operation; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

Although there have been many fuzzy object-oriented data model proposed, and a bit less for probabilistic ones, models combining the relevance and strength of both fuzzy set theory and probability theory appear to be sporadic. This paper introduces our extension of Eiter et al.'s probabilistic object base model with two key features: uncertain and imprecise attribute values are represented as probability distributions on a set of fuzzy set values; class methods with uncertain and imprecise input and output arguments are formally integrated into the new model. A probabilistic interpretation of relations on fuzzy set values is proposed for their combination with probability degrees. Then the syntax and semantics of fuzzy-probabilistic object base schemas, instances, and selection operation are defined.